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Evaluating knee forces during eccentric braking on a spinning bike
Spinning bikes are commonly used during rehabilitation in clinical settings. However, potentially high shear forces at the knee during breaking could represent a risk for certain patients. The goal of this study is to quantify the loads experienced at the knee during different cycling conditions
The understanding of joint loads during rehabilitation exercises is crucial in order to sustain the clinician's evidence-based decision making. However, there is no data available on shear force components at the knee on a spinning bike, particularly during eccentric braking, although its use has been frequently observed during rehabilitation in the clinic.
During a previous research project in our group,
20 participants performed steady-state cycling (freewheel bicycle, fixed-gear spinning bicycle) and eccentric braking (spinning bicycle) at 60-100rpm. The bicycles were instrumented with force-sensing pedals and data was acquired in combination with a camera-based motion capture system.
In order to get an accurate estimation of the forces occuring at the knee during the measured cycling conditions, the use of detailed musculoskeletal models is required.
Musculoskeletal modelling, through commercially available software such as the Anybody Modeling System, allows to calculate the required muscle activations and joint forces and moments during different motions tasks. These tools are currently gaining relevance in a broad range of scientific, clinical, and industry-related applications and they represent a suitable tool to better characterize the resulting loads on the knee joint during cycling. The student will learn the basics of musculoskeletal modelling, including the principles of inverse dynamics based on motion capture data, and understand how this knowledge can be applied to movement analysis, sport sciences, and rehabilitation programs.
The understanding of joint loads during rehabilitation exercises is crucial in order to sustain the clinician's evidence-based decision making. However, there is no data available on shear force components at the knee on a spinning bike, particularly during eccentric braking, although its use has been frequently observed during rehabilitation in the clinic. During a previous research project in our group, 20 participants performed steady-state cycling (freewheel bicycle, fixed-gear spinning bicycle) and eccentric braking (spinning bicycle) at 60-100rpm. The bicycles were instrumented with force-sensing pedals and data was acquired in combination with a camera-based motion capture system. In order to get an accurate estimation of the forces occuring at the knee during the measured cycling conditions, the use of detailed musculoskeletal models is required. Musculoskeletal modelling, through commercially available software such as the Anybody Modeling System, allows to calculate the required muscle activations and joint forces and moments during different motions tasks. These tools are currently gaining relevance in a broad range of scientific, clinical, and industry-related applications and they represent a suitable tool to better characterize the resulting loads on the knee joint during cycling. The student will learn the basics of musculoskeletal modelling, including the principles of inverse dynamics based on motion capture data, and understand how this knowledge can be applied to movement analysis, sport sciences, and rehabilitation programs.
The goal of the project is to adapt a currently existing musculoskeletal model of cycling in the AnyBody Modeling System so that it can be driven with motion capture and pedals force data previously acquired in our lab, and to perform an analysis of the knee loads experienced during various cycling conditions.
Literature review (10%)
Data preparation (10%)
Model development (40%)
Modelling-based analysis of knee loads(20%)
Results interpretation and report (20%)
The goal of the project is to adapt a currently existing musculoskeletal model of cycling in the AnyBody Modeling System so that it can be driven with motion capture and pedals force data previously acquired in our lab, and to perform an analysis of the knee loads experienced during various cycling conditions.
Literature review (10%) Data preparation (10%) Model development (40%) Modelling-based analysis of knee loads(20%) Results interpretation and report (20%)